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陳玉敏、碩士生方濤的論文在WATER刊出
發布時間:2019-12-11 16:28:07     發布者:易真     浏覽次數:

标題: Flood Risk Evaluation in the Middle Reaches of the Yangtze River Based on Eigenvector Spatial Filtering Poisson Regression

作者: Fang, T (Fang, Tao); Chen, YM (Chen, Yumin); Tan, HY (Tan, Huangyuan); Cao, JP (Cao, Jiping); Liao, JX (Liao, Jiaxin); Huang, LH (Huang, Liheng)

來源出版物: WATER  : 11  : 10  文獻号: 1969  DOI: 10.3390/w11101969  出版年: OCT 2019  

摘要: A Poisson regression based on eigenvector spatial filtering (ESF) is proposed to evaluate the flood risk in the middle reaches of the Yangtze River in China. Regression analysis is employed to model the relationship between the frequency of flood alarming events observed by hydrological stations and hazard-causing factors from 2005 to 2012. Eight factors, including elevation (ELE), slope (SLO), elevation standard deviation (ESD), river density (DEN), distance to mainstream (DIST), NDVI, annual mean rainfall (RAIN), mean annual maximum of three-day accumulated precipitation (ACC) and frequency of extreme rainfall (EXE) are selected and integrated into a GIS environment for the identification of flood-prone basins. ESF-based Poisson regression (ESFPS) can filter out the spatial autocorrelation. The methodology includes construction of a spatial weight matrix, testing of spatial autocorrelation, decomposition of eigenvectors, stepwise selection of eigenvectors and calculation of regression coefficients. Compared with the pseudo R squared obtained by PS (0.56), ESFPS exhibits better fitness with a value of 0.78, which increases by approximately 39.3%. ESFPS identifies six significant factors including ELE, DEN, EXE, DIST, ACC and NDVI, in which ACC and NDVI are the first two main factors. The method can provide decision support for flood risk relief and hydrologic station planning.

入藏号: WOS:000495598400014

語言: English

文獻類型: Article

作者關鍵詞: spatial autocorrelation; Poisson regression; eigenvector spatial filtering method; flood risk evaluation

地址: [Fang, Tao; Chen, Yumin; Tan, Huangyuan; Cao, Jiping; Liao, Jiaxin; Huang, Liheng] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China.

通訊作者地址: Chen, YM (通訊作者)Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China.

電子郵件地址: fountaintop@whu.edu.cn; ymchen@whu.edu.cn; tanhuangyuan@whu.edu.cn; caojiping@whu.edu.cn; 2018282050169@whu.edu.cn; 2014301110077@whu.edu.cn

影響因子:2.524


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